Publications des institutions partenaires
Optimisation de portefeuille: prédire rendements et risques de manière robuste
En finance, le but d'un investisseur confronté à une construction de portefeuille est de trouver quelle combinaison d'actifs produira, dans le futur, le meilleur rendement possible, et cela pour un risque donné.
Institution partenaire
Français / 01/01/2004
Bounded-Bias Robust Estimation in Generalized Linear Latent Variable Models
This paper proposes a robust estimator for a general class of linear latent variable models (GLLVM) (Moustaki and Knott 2000, Bartholomew and Knott 1999). It is based on a weighted score function that is simple to implement numerically and is made consistent using the basic idea of indirect inference. The need of a robust estimator for these models is motivated by the study of the...
Institution partenaire
English / 01/01/2004
A Latent Variable Approach for the Construction of Continuous Health Indicators
In most health survey the state of health of individuals is measured through several different kinds of variables such as qualitative, discrete quantitative or dichotomic ones. From these variables, one aims at building univariate indices of health that summarize the information. To do so, we propose in this paper to use Generalized Linear Latent Variable Models (GLLVM) (see e.g....
Institution partenaire
English / 01/01/2004
Management of non-maturing deposits by multistage stochastic programming
The management of non-maturing account positions in a bank's balance like savings and sight deposits as well as certain types of variable-rate mortgages is complicated by the embedded options that its clients may exercise. In addition to the usual interest rate risk, uncertainty in the timing and amount of cash flows must be taken into account when investment or refinancing...
Institution partenaire
English / 16/12/2003
Solving Sequences of Refined Multistage Stochastic Linear Programs
Multistage stochastic programs with continuous underlying distributions involve the obstacle of high-dimensional integrals where the integrands' values again are given by solutions of stochastic programs. A common solution technique consists of discretizing the support of the original distributions leading to scenario trees and corresponding LPs which are ? up to a certain size...
Institution partenaire
English / 01/11/2003
Modellrisiko konventioneller Ansätze - Margen verbessern
Institution partenaire
Deutsch / 01/11/2003
Energy Business and Finance Policy - Parallels in Methodology and Duties
The ongoing deregulation of electricity markets worldwide has a major impact on the power industry. New price risks require new risk management tools and new methods for the valuation of generation and transmission assets as well as existing (physical) electricity contracts. As far as risk management is concerned, many derivative instruments have been designed to hedge against spot...
Institution partenaire
Deutsch / 25/09/2003
Derivative Estimation and Testing in Generalized Additive Models
Institution partenaire
English / 01/01/2003
A Prediction Error Criterion for Choosing the Lower Quantile in Pareto Index Estimation
Successful estimation of the Pareto tail index from extreme order statistics relies heavily on the procedure used to determine the number of extreme order statistics that are used for the estimation. Most of the known procedures are based on the minimization of (an estimate of) the asymptotic mean square error of the Hill estimator for the Pareto tail index. The principal drawback of...
Institution partenaire
English / 01/01/2003
Distribution-Free Inference for Welfare Indices under Complete and Incomplete Information
The data available for estimating welfare indicators are often inconveniently incomplete data: they may be censored or truncated. Furthermore, for robustness reasons, researchers sometimes use trimmed samples. By using the statistical tool known as the Influence Function we derive distribution-free asymptotic variances for wide classes of welfare indicators not only in the complete...
Institution partenaire
English / 01/01/2003
High Breakdown Inference in the Mixed Linear Model
Mixed linear models are used to analyse data in many settings. These models have in most cases a multivariate normal formulation. The maximum likelihood estimator (MLE) or the residual MLE (REML) are usually chosen to estimate the parameters. However, the latter are based on the strong assumption of exact multivariate normality. Welsh and Richardson (1997) have shown that these...
Institution partenaire
English / 01/01/2003
Fast Algorithms for Computing High Breakdown Covariance Matrices with Missing Data
Robust estimation of covariance matrices when some of the data at hand are missing is an important problem. It has been studied by Little and Smith (1987) and more recently by Cheng and Victoria-Feser (2002). The latter propose the use of high breakdown estimators and so-called hybrid algorithms (see e.g. Woodruff and Rocke 1994). In particular, the minimum volume ellipsoid of...
Institution partenaire
English / 01/01/2003
Robust Mean-Variance Portfolio Selection
This paper investigates model risk issues in the context of mean-variance portfolio selection. We analytically and numerically show that, under model misspecification, the use of statistically robust estimates instead of the widely used classical sample mean and covariance is highly beneficial for the stability properties of the mean-variance optimal portfolios. Moreover, we perform...
Institution partenaire
English / 01/01/2003
Umsetzung stochastischer Optimierungsmethoden in der Energiewirtschaft
Institution partenaire
Deutsch / 15/05/2002
Degrees-of-freedom tests for smoothing splines
When using smoothing splines to estimate a function, the user faces the problem of choosing the smoothing parameter. Several techniques are available for selecting this parameter according to certain optimality criteria. Here, we take a different point of view and we propose a technique for choosing between two alternatives, for example allowing for two different levels of degrees of...
Institution partenaire
English / 01/01/2002
Welfare Rankings in the Presence of Contaminated Data
Stochastic dominance criteria are commonly used to draw welfare-theoretic inferences about comparisons of income distribution as well as ranking probability distributions in the analysis of choice under uncertainty. However, just as some measures of location and dispersion can be catastrophically sensitive to extreme values in the data it is also possible that conclusions drawn from...
Institution partenaire
English / 01/01/2002
High Breakdown Estimation of Multivariate Location and Scale With Missing Observations
In this paper, we consider the problem of outliers in incomplete multivariate data, when the aim is to estimate a measure of mean and covariance as it is the case for example in factor analysis. In such a situation the ER algorithm of Little and Smith (1987) which combines the EM algorithm for missing data and a robust estimation step based on an Mestimator could be used. However,...
Institution partenaire
English / 01/01/2002
Robust Inference with Binary Data
In this paper robustness properties of the maximum likelihood estimator (MLE) and several robust estimators for the logistic regression model when the responses are binary are analysed. It is found that the MLE and the classical Rao's score test can be misleading in the presence of model misspecification which in the context of logistic regression means either misclassification...
Institution partenaire
English / 01/01/2002
Robust Estimation and Inference for Generalised Latent Trait Models
The paper discusses the effect of model deviations such as data contamination on the maximum likelihood estimator (MLE) for a general class of latent trait models (citeNP{MoKn:00}). This is done with the use of the influence function (Hampel 1968, 1974) a mathematical tool to assess the robustness properties of any statistic, such as an estimator. Simulation studies show that the MLE...
Institution partenaire
English / 01/01/2002
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